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Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery Session VII Abstracts
Protein-Protein Docking and Design
Zhiping Weng
, Thom Vreven, and Brian Pierce
University of Massachusetts Medical School, Worcester, MA, USA
Protein-protein interaction is highly important for many cellular processes. We have built
computational algorithms and benchmarks to predict the 3D structures of protein-protein
complexes (protein-protein docking). I will present our recent work on both scoring function and
search algorithm to improve protein-protein docking accuracy. In addition, we have built
computational algorithms and an affinity benchmark for designing proteins to achieve stronger
and more specific binding to another protein (protein design). We have thus far focused on
designing T cell receptors and I will report on our recent progress.
Structural Networks of Signaling Pathways on Proteome Scale: Challenges and
Opportunities
Attila Gursoy
.
Koc University, Istanbul, Turkey.
Recent advances in high-throughput techniques have resulted in large amount of data on protein
structure and protein-protein interactions. Networks of protein–protein interactions provide
valuable information in understanding of cellular functions and biological processes. However,
these networks lack structural (3D) details of most interactions, and these structural details are
the key components usually for understanding the function of proteins. Augmenting protein
interaction networks with structural data at proteome scale (3D interactome) is a challenging
task, at the same time, extremely important because it allows prediction of protein function,
helps drug discovery and takes steps toward genome-wide structural systems biology. In this
talk, the challenges in building such networks will be discussed and a computationally feasible
way towards building them using protein interfaces will be presented. Structural protein
interaction networks can indicate which binding partners can interact simultaneously and which
are competitive, how signals coming from different upstream pathways merge and propagate
downstream, how multi-subunit signaling complexes form. They can help drug discovery along
the line of emerging network medicine paradigm, and can help forecasting potentially harmful
drug side effects.
